Changes in decision making are ubiquitous throughout aging. As examples, the decisions of older adults are more economically conservative and more likely to be compromised by irrelevant information. Historically, these deficits have been explained using concepts derived from behavioral research within cognitive psychology. In this application, we contend that a different, neuroeconomic approach is necessary, one that augments constructs derived from behavioral phenomena with those derived from neuroscientific research. Our approach rests on three hypotheses. First, we hypothesize that many decision-making differences between middle-aged and peri-retirement adults are the result of deficits in information integration: specifically a lack of access to source information, a difficulty in inhibiting irrelevant information, and an increased reliance on emotional information. Second, we contend that age-related deficits are manifest not only in their effects on behavior, but also in their effects on specific patterns of brain function, as younger and older adults employ different sets of cognitive competencies to solve decision problems. Third, we hypothesize that both laboratory and real-world decision behavior will be better predicted by a combination of behavioral and brain- based constructs than by either source of information alone. [unreadable] [unreadable] To test these predictions, we propose an integrated program of behavioral and functional neuroimaging research. Middle aged (40-50y) and peri-retirement (60-70y) adults will be initially screened on a variety of standard cognitive tasks. Two fMRI experiments will use an economically valid advertising paradigm, in which subjects will view a series of products accompanied by valenced facts with source attribution. One experiment will manipulate source credibility, while the other will manipulate information load. Unlike standard neuroeconomic paradigms (e.g., decisions between gambles), subjects will report their judgments about the items at a later time period (e.g., mimicking the advertising-purchasing delay). We will create regression models that include both cognitive measures of behavior and neuroscience measures of brain function, such as the degree of frontal compensation. Our critical, albeit exploratory prediction, is that both product attitudes and real world financial behavior (e.g., the risk level of the subjects' portfolios) will be best explained by using both behavioral and neuroscience constructs. [unreadable] [unreadable] The decision making of older adults is subject to many biases, from a difficulty in accurately integrating information to the increased reliance on emotional information, and these biases lead to problems in investment, health-care choice, and other economic arenas. The proposed experiments will elucidate the changes in the elderly brain that underlie decision-making biases. Better understanding of this brain-behavior relation could lead to interventions or clinical advances that remediate problems with decision making in the elderly, resulting in benefits to public health. [unreadable] [unreadable] [unreadable] [unreadable] [unreadable]